An Application of Residue Number System (RNS) to a Next-Generation Sequencing - SOLiD

Joshua Apigagua Akanbasiam *

Department of Electrical/Electronics Engineering, Dr Hilla Limann Technical University, Wa, Ghana.

Kwame Osei Boateng

Department of Computer Engineering, Kwame Nkrumah University of Science and Technology Kumasi, Ghana.

Matthew Glover Addo

Department of Theoretical and Applied Biology, Kwame Nkrumah University of Science and Technology Kumasi, Ghana.

*Author to whom correspondence should be addressed.


Abstract

Aims: This research work leverages the possibility and potential of an RNS-dibase table to generate the sequence primer and colour space for successful SOLiD sequencing. This design is flexible as compared with its binary counterpart and also presents a quaternary approach to SOLiD sequencing.

Study Design: RNS sequence primer and colour space are generated resulting in a successful RNS-SOLiD Sequencing.

Methodology: One of the most accurate Next Generation Sequencing (NGS) methods currently in use is Sequencing by Oligonucleotide Ligation and Detection (SOLiD). It combines ligation-base chemistry with a di-base labelled probe to produce an accuracy rate of about 99.9999%. RNS has the potential of generating the di-base table which is the Rosetta stone for SOLiD sequencing. Leveraging this possibility, the sequence primer and colour space which are requirements for a successful SOLiD sequencing are generated in RNS space. Following this, SOLiD sequencing is therefore designed using RNS.

Results: An RNS di-base table is presented and this serves as a look-up table for the generation of RNS sequence primer and colour space for successful SOLiD sequencing. A platform-independent algorithm is also developed that effectively illustrates SOLiD sequencing in RNS space.

Conclusion: This lays the groundwork for the incorporation of RNS into SOLiD sequencing. This design is flexible and buttresses the quest for a quaternary number system for molecular biological design and analysis.

Keywords: RNS, SOLiD, sequence primer, colour space, single nucleotide polymorphism, di-base table, measurement errors, mismatched leading base


How to Cite

Akanbasiam, Joshua Apigagua, Kwame Osei Boateng, and Matthew Glover Addo. 2024. “An Application of Residue Number System (RNS) to a Next-Generation Sequencing - SOLiD”. Asian Journal of Biotechnology and Genetic Engineering 7 (2):150-57. https://journalajbge.com/index.php/AJBGE/article/view/133.


References

Note T. Sequencing of SARS-CoV-2, no; 2020.

Cheng L, Yu T, Aittokallio T, J. Corander, R. Khalitov, and Z. Yang, Self-supervised learning for DNA Sequences with Circular Dilated Convolutional Networks. 2023;1–10.

Hong C, Cao B, Chang C, Member S, Srikanthan T, Member S. five ‑ moduli set A Residue-to-Binary Converter for a New Five-Moduli Set; 2007.

Kehinde Bello H, Alagbe Gbolagade K. Acceleration of Biological Sequence Alignment Using Residue Number System, Asian J. Res. Comput. Sci. 2018;1(2):1-10. DOI: 10.9734/ajrcos/2018/v1i224735

Sharma P, Doultani S, Hadiya K, George L, Highland H. Overview of Marker-assisted Selection in Animal Breeding. Journal of Advances in Biology & Biotechnology. 2024;27(5):303–318. Available:https://doi.org/10.9734/jabb/2024/v27i5790

Chervyakov NI, Lyakhov PA, Babenko MG. Digital filtering of images in a residue number system using finite-field wavelets. Automatic Control and Computer Sciences. 2014;48:180-9.

Daabo MI. A Hybrid Residue to Binary Converster for The Moduli Set, Int. Res. J. Eng. Technol. 2018;458–464,.

Strickland L. Leibniz: Explanation of binary arithmetic. GM 2007;7(1703):223–227. Available: http://www.leibniz-translations.com/pdf/binary.pdf.

H. Kehinde and K. Alagbe, Residue number system: An important application in bioinformatics, Int. J. Comput. Appl. 2018;179(10):28–33 DOI: 10.5120/ijca2018916106

Kari AP. An e cient image cryptosystem based on the residue number system and Hybrid chaotic maps. 2023;0–22.

KOB, Baagyere KAGY. Bioinformatics: An Important Application Area of Residue Number System; 2011.

Liu J, B Liu, Fu H. Optimizing residue number system on FPGA, Proc. - 2016 IEEE Int. Conf. Internet Things; IEEE Green Comput. Commun. IEEE Cyber, Phys. Soc. Comput. IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data. 2017;621–624. DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData. 2016;137.

Habibi N, Salehnamadi MR. An improved RNS reverse converter in three-moduli set, J. Comput. Robot. 2016;9(2): 27–32.

Bisht SS, Panda AK. DNA sequencing: Methods and Applications. 2013; 9788132215.

Kchouk M, Gibrat JF, Elloumi M. Generations of sequencing technologies: From First to Next Generation, Biol. Med. 2017;9(3):03. DOI: 10.4172/0974-8369.1000395

NCBI), The principles of DNA Sequencing; 2013.

Satam H. et al., Next-Generation Sequencing Technology: Current Trends and Advancements, Biology (Basel). 2023; 12(7):1–25. DOI: 10.3390/biology12070997

Applied biosystems, Applied Biosystems SOLiDTM 3 System Instrument Operation Guide. 2016;1–8. Available:http://tools.lifetechnologies.com/content/sfs/manuals/4407430b.pdf

Cheng C, Fei Z, Xiao P. Methods to improve the accuracy of next-generation sequencing, Front. Bioeng. Biotechnol. 2023;11:1–13. DOI: 10.3389/fbioe.2023.982111

Applied-Biosystems, Principles of Di-Base sequencing and the advantages of color space analysis in the SOLiD System, Appl. Note. 2011;2–5.